hands_onExercise3(2)

Programming Animated Statistical Graphics with R

##4.1.1 Basic concepts of animation ##4.2 Getting Started ###4.2.1 Loading the R packages

pacman::p_load(readxl, gifski, gapminder,
               plotly, gganimate, tidyverse)

###4.2.2 Importing the data

# Load libraries
library(readxl)
library(dplyr)

# Correct path
col <- c("Country", "Continent")

globalPop <- read_xls("C:\\RBSantigari-MITB\\ISSS608-VAA\\HandsonExercise\\Hands_onExercise3(2)\\data\\GlobalPopulation.xls",
                      sheet = "Data") %>%
  mutate(across(all_of(col), factor)) %>%
  mutate(Year = as.integer(Year))

###Unfortunately, mutate_each_() was deprecated in dplyr 0.7.0. and funs() was deprecated in dplyr 0.8.0. In view of this, we will re-write the code by using mutate_at() as shown in the code chunk below.###

col <- c("Country", "Continent")
globalPop <- read_xls("C:\\RBSantigari-MITB\\ISSS608-VAA\\HandsonExercise\\Hands_onExercise3(2)\\data\\GlobalPopulation.xls", sheet = "Data") %>%
  mutate_at(col, as.factor) %>%
  mutate(Year = as.integer(Year))

###Instead of using mutate_at(), across() can be used to derive the same outputs.###

col <- c("Country", "Continent")
globalPop <- read_xls("C:\\RBSantigari-MITB\\ISSS608-VAA\\HandsonExercise\\Hands_onExercise3(2)\\data\\GlobalPopulation.xls", sheet = "Data") %>%
  mutate(across(all_of(col), as.factor)) %>%
  mutate(Year = as.integer(Year))

##4.3 Animated Data Visualisation: gganimate methods ###4.3.1 Building a static population bubble plot

ggplot(globalPop, aes(x = Old, y = Young, 
                      size = Population, 
                      colour = Country)) +
  geom_point(alpha = 0.7, 
             show.legend = FALSE) +
  scale_colour_manual(values = country_colors) +
  scale_size(range = c(2, 12)) +
  labs(title = 'Year: {frame_time}', 
       x = '% Aged', 
       y = '% Young') 

###4.3.2 Building the animated bubble plot

ggplot(globalPop, aes(x = Old, y = Young, 
                      size = Population, 
                      colour = Country)) +
  geom_point(alpha = 0.7, 
             show.legend = FALSE) +
  scale_colour_manual(values = country_colors) +
  scale_size(range = c(2, 12)) +
  labs(title = 'Year: {frame_time}', 
       x = '% Aged', 
       y = '% Young') +
  transition_time(Year) +       
  ease_aes('linear')          

##4.4 Animated Data Visualisation: plotly ###4.4.1 Building an animated bubble plot: ggplotly() method

gg <- ggplot(globalPop, 
       aes(x = Old, 
           y = Young, 
           size = Population, 
           colour = Country)) +
  geom_point(aes(size = Population,
                 frame = Year),
             alpha = 0.7, 
             show.legend = FALSE) +
  scale_colour_manual(values = country_colors) +
  scale_size(range = c(2, 12)) +
  labs(x = '% Aged', 
       y = '% Young')

Warning in geom_point(aes(size = Population, frame = Year), alpha = 0.7, :
Ignoring unknown aesthetics: frame

ggplotly(gg)

Warning in p$x$data[firstFrame] <- p$x$frames[[1]]$data: number of items to
replace is not a multiple of replacement length

#Notice that although show.legend = FALSE argument was used, the legend still appears on the plot. To overcome this problem, theme(legend.position=‘none’) should be used as shown in the plot and code chunk below#

gg <- ggplot(globalPop, 
       aes(x = Old, 
           y = Young, 
           size = Population, 
           colour = Country)) +
  geom_point(aes(size = Population,
                 frame = Year),
             alpha = 0.7) +
  scale_colour_manual(values = country_colors) +
  scale_size(range = c(2, 12)) +
  labs(x = '% Aged', 
       y = '% Young') + 
  theme(legend.position='none')

Warning in geom_point(aes(size = Population, frame = Year), alpha = 0.7):
Ignoring unknown aesthetics: frame

ggplotly(gg)

Warning in p$x$data[firstFrame] <- p$x$frames[[1]]$data: number of items to
replace is not a multiple of replacement length

###4.4.2 Building an animated bubble plot: plot_ly() method

bp <- globalPop %>%
  plot_ly(x = ~Old, 
          y = ~Young, 
          size = ~Population, 
          color = ~Continent,
          sizes = c(2, 100),
          frame = ~Year, 
          text = ~Country, 
          hoverinfo = "text",
          type = 'scatter',
          mode = 'markers'
          ) %>%
  layout(showlegend = FALSE)
bp

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